The National COVID Cohort Collaborative (N3C): Rationale, design, infrastructure, and deployment.

OBJECTIVE: Coronavirus disease 2019 (COVID-19) poses societal challenges that require expeditious data and knowledge sharing. Though organizational clinical data are abundant, these are largely inaccessible to outside researchers. Statistical, machine learning, and causal analyses are most successful with large-scale data beyond what is available in any given organization. Here, we introduce the National COVID Cohort Collaborative (N3C), an open science community focused on analyzing patient-level data from many centers. MATERIALS AND METHODS: The Clinical and Translational Science Award Program and scientific community created N3C to overcome technical, regulatory, policy, and governance barriers to sharing and harmonizing individual-level clinical data. We developed solutions to extract, aggregate, and harmonize data across organizations and data models, and created a secure data enclave to enable efficient, transparent, and reproducible collaborative analytics. RESULTS: Organized in inclusive workstreams, we created legal agreements and governance for organizations and researchers; data extraction scripts to identify and ingest positive, negative, and possible COVID-19 cases; a data quality assurance and harmonization pipeline to create a single harmonized dataset; population of the secure data enclave with data, machine learning, and statistical analytics tools; dissemination mechanisms; and a synthetic data pilot to democratize data access. CONCLUSIONS: The N3C has demonstrated that a multisite collaborative learning health network can overcome barriers to rapidly build a scalable infrastructure incorporating multiorganizational clinical data for COVID-19 analytics. We expect this effort to save lives by enabling rapid collaboration among clinicians, researchers, and data scientists to identify treatments and specialized care and thereby reduce the immediate and long-term impacts of COVID-19

New Timing and Depth Constraints for the Catalina Metamorphic Core Complex, Southeast Arizona

The Santa Catalina-Tortolita-Rincon Mountains of Southeast Arizona are a classic metamorphic core complex (MCC) and represent footwall exposures of crustal rocks exhumed by a detachment system. This study presents new evidence for the formation of the majority of ductile deformation during the Eocene (similar to 46 Ma), synchronous with the emplacement of the regionally significant Wilderness Sills Suite (57-45 Ma). The evidence is provided by Eocene U-Pb ages of syn- to late kinematic dikes emplaced in the principal ductile mylonitic fabric of the Catalina forerange, earlier than the brittle normal fault system and the formation of Tucson basin beginning with the latest Oligocene. Well-documented shear sense indicators may not reflect extension at that time (Eocene), but more likely the direction of crustal flow now rotated during later extension. Muscovite-plagioclase Rb-Sr isochron ages of three mylonitic rocks are all clustered around 34 Ma, which is inferred to be the last age when these rocks were being deformed under ductile conditions following the emplacement of the Wilderness Sills Suite and various related dikes. Biotite-plagioclase Rb-Sr ages on the same rocks demonstrate that the section cooled below similar to 300 degrees C at 25-26 Ma during the development of normal faulting. Normal faulting was synchronous with the emplacement of the Catalina Intrusive Suite. New U-Pb age results for Catalina Intrusive Suite indicate a combined mean age of 24.9 Ma. Chemical compositions of hornblende-plagioclase pairs were obtained on six Catalina Intrusive Suite samples; depth estimates for the emplacement of the Catalina Intrusive Suite average of about 6 km. These results suggest that the exposed Catalina ductile detachment system was at about 5 km beneath the surface at 25 Ma. These new data bring new light into the development of this core complex and suggest that the similarity in orientations ofprincipalductile and brittle fabrics at the Catalina MCC locality are coincidental. Neither was the principal ductile fabric developed during the low-angle normal faulting of the latest Oligocene nor was this exposed section a midcrustal one at that time. Transient, pluton emplacement-enhanced, and extension-related ductile deformation at shallow crustal levels operated locally at similar to 25 Ma but that does not account for the development of the majority of the Catalina MCC mylonites.6 month embargo; first published online 15 August 2020This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

The National COVID Cohort Collaborative (N3C): Rationale, Design, Infrastructure, and Deployment

ObjectiveCoronavirus disease 2019 (COVID-19) poses societal challenges that require expeditious data and knowledge sharing. Though organizational clinical data are abundant, these are largely inaccessible to outside researchers. Statistical, machine learning, and causal analyses are most successful with large-scale data beyond what is available in any given organization. Here, we introduce the National COVID Cohort Collaborative (N3C), an open science community focused on analyzing patient-level data from many centers.Materials and methodsThe Clinical and Translational Science Award Program and scientific community created N3C to overcome technical, regulatory, policy, and governance barriers to sharing and harmonizing individual-level clinical data. We developed solutions to extract, aggregate, and harmonize data across organizations and data models, and created a secure data enclave to enable efficient, transparent, and reproducible collaborative analytics.ResultsOrganized in inclusive workstreams, we created legal agreements and governance for organizations and researchers; data extraction scripts to identify and ingest positive, negative, and possible COVID-19 cases; a data quality assurance and harmonization pipeline to create a single harmonized dataset; population of the secure data enclave with data, machine learning, and statistical analytics tools; dissemination mechanisms; and a synthetic data pilot to democratize data access.ConclusionsThe N3C has demonstrated that a multisite collaborative learning health network can overcome barriers to rapidly build a scalable infrastructure incorporating multiorganizational clinical data for COVID-19 analytics. We expect this effort to save lives by enabling rapid collaboration among clinicians, researchers, and data scientists to identify treatments and specialized care and thereby reduce the immediate and long-term impacts of COVID-19

The Neogene tropical America fish assemblage and the paleobiogeography of the Caribbean region

This first analysis of the marine fish fossil record in the Caribbean region during the Neogene is based on comprehensive new faunal compilation lists at the generic level from basins of nine Central and South American countries during Miocene and Pliocene times. Joint ordination and classification techniques were used to analyze data comprising 236 genera and 346 species. Principal Component Analyses were used to calculate covariance and variance between localities. We identified four subprovinces, representing four different patterns. The subprovince of Venezuela shows distinct and unique features since the Neogene in the diversity of ecosystems represented. The Antillean subprovince has a western orientation and is composed of Jamaica, the Dominican Republic, and the Trinidad islands. The third subprovince combines Panama and Ecuador. It reflects the Pacific faunal influence into the proto-Caribbean and a characteristic benthopelagic fauna. The fourth subprovince is Costarican. Its nektonic fish fauna reflects the overprinting impact over the proto-Caribbean fish fauna mostly due to local paleoenvironmental changes (neritic, estuarine and deep water assemblages), whereby the overall composition of genera is largely not affected (except few lamnids, such as the giant-toothed white sharks and the wide-toothed mako shark). The results of the analyses are concordant with previous ones based on invertebrates and identified regions in need of study (e.g., Colombia, Nicaragua, Honduras, and Brazil)